Multiyear Discrete Stochastic Programming with a Fuzzy Semi-Markov Process

Drought conditions at a given location evolve randomly through time and are typically characterized by severity and duration. Researchers interested in modeling the economic effects of drought on agriculture or other water users often capture the stochastic nature of drought and its conditions via multiyear, stochastic economic models. Three major sources of uncertainty in application of a multiyear discrete stochastic model to evaluate user preparedness and response to drought are: (1) the assumption of independence of yearly weather conditions, (2) linguistic vagueness in the definition of drought itself, and (3) the duration of drought. One means of addressing these uncertainties is to re-cast drought as a stochastic, multiyear process using a “fuzzy” semi-Markov process. In this paper, we review “crisp” versus “fuzzy” representations of drought and show how fuzzy semi-Markov processes can aid researchers in developing more robust multiyear, discrete stochastic models.

Stability Estimation for Markov Control Processes with Discounted Cost

This article explores controllable Borel spaces, stationary, homogeneous Markov processes, discrete time with infinite horizon, with bounded cost functions and using the expected total discounted cost criterion. The problem of the estimation of stability for this type of process is set. The central objective is to obtain a bounded stability index expressed in terms of the Lévy-Prokhorov metric;likewise, sufficient conditions are provided for the existence of such inequalities.

Asymptotic Evaluations of the Stability Index for a Markov Control Process with the Expected Total Discounted Reward Criterion

In this work, for a control consumption-investment process with the discounted reward optimization criteria, a numerical estimate of the stability index is made. Using explicit formulas for the optimal stationary policies and for the value functions, the stability index is explicitly calculated and through statistical techniques its asymptotic behavior is investigated (using numerical experiments) when the discount coefficient approaches 1. The results obtained define the conditions under which an approximate optimal stationary policy can be used to control the original process.

基于离散Markov决策过程的发电公司多阶段决策

采用离散时间Markov决策过程(DTMDP)对以多阶段总利润最优为目标的发电公司决策问题进行研究.市场环境下,发电公司根据自身条件,其竞争策略可以是价格的接受者,也可以是价格的制定者.考虑了发电公司不同策略情况下市场均衡状态间的转换概率,分别给出了发电公司作为价格接受者和价格制定者时的多阶段决策模型.通过算例验证了所提模型的有效性和可行性.

共和盆地天然草地牧草产量的Markov预测模型

Markov预测技术是应用Markov链的相关预测的基本原理与方法来研究分析时间序列的变化规律,并预测未来变化趋势的一种预报方法,适用于随机波动较大的预报问题。根据Markov链原理,提出了用于共和盆地温性草原类天然草地年平均牧草产量预报的离散随机过程模型。实测资料的验证结果表明,这种模型计算精度较高,具有良好的应用价值。

Design of Anti-Collision Integrated Security Mechanism Based on Chaotic Sequence in UHF RFID System

Collision and security issues are considered as barriers to RFID applications.In this paper,a parallelizable anti-collision based on chaotic sequence combined dynamic frame slotted aloha to build a high-efficiency RFID system is proposed.In the tags parallelizable identification,we design a Discrete Markov process to analyze the success identification rate.Then a mutual authentication security protocol merging chaotic anti-collision is presented.The theoretical analysis and simulation results show that the proposed identification scheme has less than 45.1%of the identification time slots compared with the OVSF-system when the length of the chaos sequence is 31.The success identification rate of the proposed chaotic anti-collision can achieve 63%when the number of the tag is100.We test the energy consumption of the presented authentication protocol,which can simultaneously solve the anti-collision and security of the UHF RFID system.

考虑软件运行的软-硬件退化系统剩余寿命估计

针对软-硬件系统级剩余寿命估计难题,传统的研究方法都是单独考虑了软件可靠性或硬件可靠性,而忽略了软件与硬件之间的交互影响。文中基于硬件性能退化过程提出了一种将软件的使用或运行看作是系统的一种外部冲击的新方法。该方法通过硬件性能退化指标来表征软件运行对系统的影响,主要采用离散隐Markov过程来描述两者之间的关系。具体地,对信号数据采用信号分解与特征提取技术得到性能退化指标,运用隐Markov模型构建隐含状态与实际退化之间的对应关系。根据在不同软件运行条件下系统性能退化指标样本中的拐点个数,对同一硬件退化过程分段构建不同的退化模型,使模型更加精确地描述退化过程。采用随机仿真技术与优化技术对硬件剩余寿命进行估计,根据系统体系结构估计软-硬件系统的剩余寿命。利用某武器装备系统的性能监测数据,将所提算法与传统系统级剩余寿命估计模型(BP神经网络)进行对比,证明了所提算法具有较高的估计精度。

Analysis of DAR(1)/D/s Queue with Quasi-Negative Binomial-II as Marginal Distribution

In this paper we consider the arrival process of a multiserver queue governed by a discrete autoregressive process of order 1 [DAR(1)] with Quasi-Negative Binomial Distribution-II as the marginal distribution. This discrete time multiserver queueing system with autoregressive arrivals is more suitable for modeling the Asynchronous Transfer Mode(ATM) multiplexer queue with Variable Bit Rate (VBR) coded teleconference traffic. DAR(1) is described by a few parameters and it is easy to match the probability distribution and the decay rate of the autocorrelation function with those of measured real traffic. For this queueing system we obtained the stationary distribution of the system size and the waiting time distribution of an arbitrary packet with the help of matrix analytic methods and the theory of Markov regenerative processes. Also we consider negative binomial distribution, generalized Poisson distribution, Borel-Tanner distribution defined by Frank and Melvin(1960) and zero truncated generalized Poisson distribution as the special cases of Quasi-Negative Binomial Distribution-II. Finally, we developed computer programmes for the simulation and empirical study of the effect of autocorrelation function of input traffic on the stationary distribution of the system size as well as waiting time of an arbitrary packet. The model is applied to a real data of number of customers waiting for checkout in an airport and it is established that the model well suits this data.

Convergence of Markov decision processes with constraints and state-action dependent discount factors

This paper is concerned with the convergence of a sequence of discrete-time Markov decision processes(DTMDPs)with constraints,state-action dependent discount factors,and possibly unbounded costs.Using the convex analytic approach under mild conditions,we prove that the optimal values and optimal policies of the original DTMDPs converge to those of the"limit"one.Furthermore,we show that any countablestate DTMDP can be approximated by a sequence of finite-state DTMDPs,which are constructed using the truncation technique.Finally,we illustrate the approximation by solving a controlled queueing system numerically,and give the corresponding error bound of the approximation.

互联电网CPS调节指令动态最优分配Q–学习算法

控制性能标准(control performance standard,CPS)下互联电网调度端的自动发电控制(automatic generation control,AGC)指令(简称CPS指令)到各类型AGC机组的动态优化分配是随机最优问题。将CPS指令分配的连续控制过程离散化,并可将其看作是一个离散时间马尔可夫决策过程,提出应用基于Q–学习的动态控制方法。根据优化目标的差异,设计不同的奖励函数,并将其引入到算法当中,有效结合水、火电机组的调节特性,并考虑水电机组的调节裕度,提高AGC系统调节能力。遗传算法和工程实用方法在标准两区域模型及南方电网模型的仿真研究显示,Q–学习有效提高了系统的适应性、鲁棒性和CPS考核合格率。

基于三轴加速度传感器的手势识别

针对手势交互中手势信号的相似性和不稳定性,设计实现一种基于三轴加速度传感器的手势识别方案。采用MMA7260加速度传感器采集主手腕的手势动作信号,根据手势加速度信号的特点,进行手势动作数据窗口的自动检测、信号去噪和重采样等预处理,通过提取手势动作的关键特征,构造离散隐马尔可夫模型,实现手势动作识别。实验结果证明该方案的识别精度较高。

基于马尔科夫决策的目标选择策略

目标选择是军事计划的关键要素之一。基于马尔科夫决策方法,解决具有复杂目标间关联的多阶段目标选择问题。使用与或树描述目标体系各层状态间的影响关联,并以目标体系整体失效为求解目的,建立了基于离散时间MDP的多阶段打击目标选择模型。在LRTDP算法基础上提出一种启发式方法,通过判断从当前目标体系状态到达体系失效状态的演化过程中的可能资源消耗和失败概率,来提供对当前状态的评估值,该方法能有效排除问题搜索空间中不能到达体系失效目的的中间状态,压缩了由于目标间复杂关联而增长的巨大状态空间。用实验验证了该方法有效性,实验结果表明,该方法直观实用,对目标间具有复杂关联关系的目标打击决策有一定参考价值。

基于近似动态规划的模具项目调度

模具制造工程中普遍存在任务工期不确定,以及多并行项目共享和竞争企业有限资源的情形,目前尚缺乏求解这类项目调度问题的方法。鉴于此,考虑了部分任务工期服从已知离散分布下的模具项目调度问题,基于马尔可夫决策过程理论构建了以总加权拖期成本期望最小为优化目标的数学模型。针对传统随机动态规划在求解大规模问题时面临的维数灾,分别提出了基于经典优先规则、遗传算法和近似动态规划的求解方法。通过随机生成的项目算例验证了所构建模型和方法的有效性。结果表明,所提近似方法能够在耗费较少计算资源的情形下获得可接受的次优或最优解,可用于求解工程实际问题。

基于面向对象的信息系统风险评估方法

风险评估是信息系统安全保证的核心和关键。对现有的风险评估方法进行分析评价,将面向对象的系统分析思想引入信息系统的风险评估中,完善了系统风险评估方法。能够在信息系统建设初期确定系统中关键的、高风险组件或子系统,可有效指导系统安全防护工作的经济高效开展。

有优先权两部件离散时间温贮备可修系统

在开关完全可靠的情况下,研究由两个不同型、有优先权的部件和一个修理设备组成的温贮备系统,建立在部件工作寿命和修理时间均服从几何分布的可修模型,并利用Markov过程、母函数、LS变换推导出该模型的一些可靠性指标——系统的稳态可用度及系统的首次故障前平均工作时间.

基于马尔科夫过程的钢骨混凝土耐久性预测

为了保证钢骨混凝土结构在服役期内完成的预定功能,掌握钢骨混凝土结构的退化过程,需要对钢骨混凝土结构进行预测。在总结国内外资料的基础上,运用时间连续状态离散马尔科夫过程的齐次泊松和非齐次泊松理论,给出了相关概念,总结了钢骨混凝土结构的预测过程,并采用算例实现了钢骨混凝土结构耐久性的预测,得到了等级与时间的关系曲线。研究结果表明:齐次泊松和非齐次泊松的预测结果相近,都是时间随着等级的增加而增加,预测结果也比较准确可靠。

基于马氏决策过程的概率离散事件系统最优控制

使用马氏决策过程研究了概率离散事件系统的最优控制问题.首先,通过引入费用函数、目标函数以及最优函数的定义,建立了可以确定最优监控器的最优方程.之后,又通过此最优方程获得了给定语言的极大可控、∈-包含闭语言.最后给出了获得最优费用与最优监控器的算法.

离散时间单重休假冷储备系统的可靠性分析

利用离散向量Markov过程方法研究了离散时间单重休假两同型部件冷储备可修系统。在部件寿命服从几何分布,修理时间和修理工休假时间服从一般离散型概率分布的假定下,引入修理时间和休假时间尾概率,求得了系统的稳态可用度、稳态故障频度、待修概率、修理工空闲概率和休假概率,以及首次故障前平均时间等可靠性指标。

基于可恢复冲击效应的继电器可靠性评估方法

继电器是航天器等系统的关键元件之一,精准评估其可靠性对保证全系统的安全稳定至关重要。现有继电器可靠性研究未考虑在材料和环境等因素的影响下,性能状态冲击性变化存在可恢复性的特点,可能会造成评估结果不准确。为解决此问题,综合考虑各性能参数的自然退化过程、可恢复冲击效应、退化相关性,基于维纳过程和离散时间马尔可夫链的建模理论,提出了适用于继电器的退化和冲击模型。进而,针对同时估计模型全部参数存在困难的问题,提出了一种多阶段的模型参数估计方法。并且,针对可靠性评估,提出了一种基于蒙特卡洛技术的可靠度近似计算方法。结果表明,所提出的可靠性评估方法精度较高,其拟合优度为0.1037,比现有方法提高了约70%。

基于马尔可夫电池模型的节能调度算法研究

对于电池供电的便携式系统,电池的节能调度是提高系统性能的重要因素,而建立精确实用的电池模型是研究电池节能调度算法的必要前提。提出了一种电池建模方法,即在每个单位时间内模拟电池的基本行为,通过行为的叠加实现对电池整个放电过程的跟踪。仿真和实验结果均证明了建模方法的正确性,同时亦表明方法具有建模简单、模型精度较高等优点。针对现有的电池节能算法往往存在增加系统复杂度、影响系统实时性等缺点,文中提出两种改进的电池节能调度算法,并在电池模型上进行了仿真验证。结果显示,改进后的算法更易于实现,且在满足系统实时性能前提下,达到较好的节能效果。